2017 IEEE 14th International Conference on Networking, Sensing and Control (ICNSC)最新文献_第5页

Adaptive tracking control for nonlinear systems by an adaptive model-based FNNs sliding mode control scheme 采用基于自适应模型的fnn滑模控制方案对非线性系统进行自适应跟踪控制

2017 IEEE 14th International Conference on Networking, Sensing and Control (ICNSC) Pub Date : 2017-05-01 DOI: 10.1109/ICNSC.2017.8000188

Yu‐Chen Lin, Tsung-Chih Lin, Yi-Chao Chen, I-chun Kuo

引用次数: 7

Low latency disturbance detection using distributed optical fiber sensors 分布式光纤传感器的低延迟干扰检测

2017 IEEE 14th International Conference on Networking, Sensing and Control (ICNSC) Pub Date : 2017-05-01 DOI: 10.1109/ICNSC.2017.8000121

Daniel M. Muñoz Arboleda, C. Franciscangelis, W. Margulis, F. Fruett, I. Söderquist

引用次数: 2

Evaluating weightless neural networks for bias identification on news 评估新闻偏见识别的无权重神经网络

2017 IEEE 14th International Conference on Networking, Sensing and Control (ICNSC) Pub Date : 2017-05-01 DOI: 10.1109/ICNSC.2017.8000101

Rafael Dutra Cavalcanti, P. Lima, M. D. Gregorio, D. Menasché

引用次数: 6

A swarm of wheeled and aerial robots for environmental monitoring 一群用于环境监测的轮式和空中机器人

2017 IEEE 14th International Conference on Networking, Sensing and Control (ICNSC) Pub Date : 2017-05-01 DOI: 10.1109/ICNSC.2017.8000073

M. Carpentiero, L. Gugliermetti, M. Sabatini, G. Palmerini

{"title":"A swarm of wheeled and aerial robots for environmental monitoring","authors":"M. Carpentiero, L. Gugliermetti, M. Sabatini, G. Palmerini","doi":"10.1109/ICNSC.2017.8000073","DOIUrl":"https://doi.org/10.1109/ICNSC.2017.8000073","url":null,"abstract":"The increasing interest about the environment and the conditions for a safe and healthy life require continuous monitoring of physical and chemical parameters in the urban areas as well as in specifically dangerous surroundings (proximity of plants and hazard sites). Aside from the important consideration about risk and protection of the monitoring crew, the costs of extensive, specialist operators have also to be taken into account. In such a frame, autonomous vehicles could conveniently carry on the repetitive measurements with a significant reduction in risk and costs. Looking specifically at the quality of the air, both terrestrial and aerial platforms could be used; yet the best solution would be their combined use. This research proposes indeed a monitoring system composed by wheeled rover, obviously extendable to more vehicles. These platforms map the state and the evolution of the pollution by means of a set of sensors (measuring LPE, CO, CO2, CH4, H2, NH4) purposely developed. A special focus is devoted to the autonomous guidance and navigation system, including inertial measurement unit, GPS and stereo vision that enables the operations.","PeriodicalId":145129,"journal":{"name":"2017 IEEE 14th International Conference on Networking, Sensing and Control (ICNSC)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115483730","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 14

Differential privacy data publishing method based on cell merging 基于单元合并的差分隐私数据发布方法

2017 IEEE 14th International Conference on Networking, Sensing and Control (ICNSC) Pub Date : 2017-05-01 DOI: 10.1109/ICNSC.2017.8000189

Qi Li, Yuqiang Li, Guicai Zeng, Aihua Liu

引用次数: 5

Modeling Coordinated Multipoint with a dynamic Coordination Station in LTE-A mobile networks LTE-A移动网络中基于动态协调站的协调多点建模

2017 IEEE 14th International Conference on Networking, Sensing and Control (ICNSC) Pub Date : 2017-05-01 DOI: 10.1109/ICNSC.2017.8000194

Gabriel A. Wainer, Mohammad Etemad, B. U. Kazi

引用次数: 4

HealthMate: Smart Wearable System for Health Monitoring (SWSHM) 健康伴侣:健康监测智能可穿戴系统(SWSHM)

2017 IEEE 14th International Conference on Networking, Sensing and Control (ICNSC) Pub Date : 2017-05-01 DOI: 10.1109/ICNSC.2017.8000185

Rebaz Mohammed Dler Omer, N. Al-Salihi

{"title":"HealthMate: Smart Wearable System for Health Monitoring (SWSHM)","authors":"Rebaz Mohammed Dler Omer, N. Al-Salihi","doi":"10.1109/ICNSC.2017.8000185","DOIUrl":"https://doi.org/10.1109/ICNSC.2017.8000185","url":null,"abstract":"For the recent few years, Smart Wearable Systems (SWS) have been one of the most productive areas that can be considered for clinical utilization. They are an end-to-end connected source and sink (aggregator) nodes implemented to be in communication together either locally or remotely. However, a number of these sensors can be integrated on the Wireless Body Area Networks (WBAN), which is a new method for health monitoring. In particular, technology has become a trend that affect the patients' needs for requesting an innovation, low cost and flexible system in order to be aware in the change of their physiological and non-physiological body parameters. To provide this demand, HealthMate system is proposed as a solution for real-time health monitoring system that is based on Smart Wearable System for Health Monitoring (SWSHM). This paper is aimed at providing a health monitoring system for patients to measure their body parameters through e-Health sensors via smart phone and enabling doctors to check the health status of their patients remotely. Our solution allows patients to measure their body physiological and non-physiological parameters using body temperature, electrocardiogram, pulse and oxygen in blood, airflow and body position sensors. In addition, by using internet technologies, XBee wireless (802.15.4), and SMS to transmit measured patients body parameters to either mobile application or database on a cloud server, where artificial intelligence is accomplished to examine the data in order to notify health professions in emergency case using SMS services or e-mail.","PeriodicalId":145129,"journal":{"name":"2017 IEEE 14th International Conference on Networking, Sensing and Control (ICNSC)","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124787618","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 13

Bandwidth issues in IP based lighting controls 基于IP的照明控制中的带宽问题

2017 IEEE 14th International Conference on Networking, Sensing and Control (ICNSC) Pub Date : 2017-05-01 DOI: 10.1109/ICNSC.2017.8000156

Walter Werner

引用次数: 0

Logic Programming as a Service (LPaaS): Intelligence for the IoT 逻辑编程即服务(LPaaS):物联网的智能

2017 IEEE 14th International Conference on Networking, Sensing and Control (ICNSC) Pub Date : 2017-05-01 DOI: 10.1109/ICNSC.2017.8000070

Roberta Calegari, E. Denti, S. Mariani, Andrea Omicini

引用次数: 11

Effect of linear biases in latent factor models on high-dimensional and sparse matrices from recommender systems 来自推荐系统的高维和稀疏矩阵的潜在因素模型线性偏差的影响

2017 IEEE 14th International Conference on Networking, Sensing and Control (ICNSC) Pub Date : 2017-05-01 DOI: 10.1109/ICNSC.2017.8000141

Ye Yuan, Xin Luo, Mingsheng Shang, Xin-Yi Cai

{"title":"Effect of linear biases in latent factor models on high-dimensional and sparse matrices from recommender systems","authors":"Ye Yuan, Xin Luo, Mingsheng Shang, Xin-Yi Cai","doi":"10.1109/ICNSC.2017.8000141","DOIUrl":"https://doi.org/10.1109/ICNSC.2017.8000141","url":null,"abstract":"Latent factor (LF)-based models have been proven to be efficient in implementing recommender systems, owing to their ability to well represent high-dimensional and sparse matrices. While prior works focus on boosting both the prediction accuracy and computation efficiency of original LF model by adding linear biases to it, the individual and combinational effects by linear biases in such performance gain remains unclear. To address this issue, this work thoroughly investigates the effect of prior linear biases and training linear biases. We have investigated the parameter update rules and training processes of an LF model with different combinations of linear biases. Empirical validations are conducted on a high dimensional and sparse matrix from industrial systems currently in use. The results show that each linear bias does have positive/negative effects in the performance of an LF model. Such effects are partially data dependent; however, some linear biases like the global average can bring stable performance gain into an LF model. The theoretical and empirical results along with analysis provide guidance in designing the bias scheme in an LF model for recommender systems.","PeriodicalId":145129,"journal":{"name":"2017 IEEE 14th International Conference on Networking, Sensing and Control (ICNSC)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121487731","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1